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Epileptic seizures from abnormal networks: why some seizures defy predictability
William S Anderson1, Feraz Azhar, Pawel Kudela
1The Johns Hopkins University School of Medicine, Department of Neurosurgery, 600 North Wolfe Street, Baltimore, MD 21287, USA. wanders5@jhmi.edu
Epilepsy Research
|December 16, 2011
Summary
Fluctuations in surrounding brain activity can trigger seizures in abnormal focal epileptic networks. This computational model suggests a mechanism for seizure generation, explaining challenges in predicting partial seizures.
Area of Science:
- Computational neuroscience
- Epilepsy research
- Dynamical systems theory
Background:
- Seizure prediction remains challenging in clinical settings.
- Cortical firing fluctuations may influence seizure onset in focal zones.
- Understanding ictal generation in abnormal epileptic networks is crucial.
Purpose of the Study:
- To investigate if fluctuations in cortical firing can initiate seizures in a simulated ictal zone.
- To explore the role of background input in seizure generation within computational models.
- To analyze the dynamics of bursting phases in a model of abnormal cortical connectivity.
Main Methods:
- Utilized neural network simulations in a computational cortex model (65,536 neurons).
- Applied spatially distributed Poisson-driven background input to mimic neighboring cortical activity.
- Performed statistical analyses (Gamma distribution fitting, non-parametric randomness tests) and dynamical systems analysis.
Main Results:
- Non-parametric analysis indicated intervals were randomly drawn from their distribution.
- Dynamical systems analysis supported a nondeterministic interpretation of bursting phase generation.
- Simulations demonstrated that input fluctuations can initiate seizure activity in abnormal networks.
Conclusions:
- Input fluctuations from surrounding regions can initiate seizure activity in abnormal focal epileptic networks.
- This mechanism offers a potential explanation for ictal generation in focal epilepsy.
- The findings may help explain the difficulty in predicting partial seizures in some patients.
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